Computing Education in the Era of Generative AI

Rethinking Computer Science Education from a Test-First Perspective. In Companion of the 18th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA ’03) . Association for Computing Machinery, New York, NY, USA, 148–155

Stephen H. Edwards. 2003 · 2003

Earlier work this paper cites.

Novice Java Programmers’ Conceptions of “Object” and “Class”, and Variation Theory. In Proceedings of the 10th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education (ITiCSE ’05) . Association for Computing Machinery, NY NY, USA, 89–93

Anna Eckerdal and Michael Thuné. 2005 · 2005

Earlier work this paper cites.

Code Classification as a Learning and Assessment Exercise for Novice Programmers. In 19th Annual Conference of the National Advisory Committee on Computing Qualifications (NACCQ 2006) . National Advisory Comittee on Computing Qualifications, Wellington, New Zealand, 291–298

Errol Thompson, Jacqueline Whalley, RF Lister, and Beth Simon. 2006 · 2006

Earlier work this paper cites.

Extreme apprenticeship method in teaching programming for beginners. In Proceedings of the 42nd ACM technical symposium on Computer science education . 93–98

Arto Vihavainen, Matti Paksula, and Matti Luukkainen. 2011 · 2011

Earlier work this paper cites.

Negotiating the Maze of Academic Integrity in Computing Education. In Proceedings of the 2016 ITiCSE Working Group Reports (ITiCSE ’16) . Association for Computing Machinery, NY NY, USA, 57–80

Simon, Judy Sheard, Michael Morgan, Andrew Petersen, Amber Settle, et al · 2016

Earlier work this paper cites.

Introductory Programming: A Systematic Literature Review. In Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE 2018 Companion) . Association for Computing Machinery, New York, NY, USA, 55–106

Andrew Luxton-Reilly, Simon, Ibrahim Albluwi, Brett A. Becker, Michail Giannakos, et al · 2018

Earlier work this paper cites.

Compiler Error Messages Considered Unhelpful: The Landscape of Text-Based Programming Error Message Research. In Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education (ITiCSE-WGR ’19) . Association for Computing Machinery, New York, NY,USA, 177–210

Brett A. Becker, Paul Denny, Raymond Pettit, Durell Bouchard, Dennis J. Bouvier, et al · 2019

Earlier work this paper cites.

50 Years of CS1 at SIGCSE: A Review of the Evolution of Introductory Programming Education Research. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE ’19) . Association for Computing Machinery, New York, NY, USA, 338–344

Brett A. Becker and Keith Quille. 2019 · 2019

Earlier work this paper cites.

A Review of Peer Code Review in Higher Education

Theresia Devi Indriasari, Andrew Luxton-Reilly, and Paul Denny. 2020 · 2020

Earlier work this paper cites.

What Does Saying That ‘Programming is Hard’ Really Say, and About Whom?

Brett A. Becker. 2021 · 2021

Earlier work this paper cites.

On the Opportunities and Risks of Foundation Models

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, et al · 2021

Earlier work this paper cites.

Evaluating Large Language Models Trained on Code

Original

Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, et al · 2021

Earlier work this paper cites.

Plagiarism in the Age of Massive Generative Pre-trained Transformers (GPT-3)

Nassim Dehouche. 2021 · 2021

Earlier work this paper cites.

On Designing Programming Error Messages for Novices: Readability and Its Constituent Factors. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (CHI ’21) . Association for Computing Machinery, New York, NY,USA, Article 55, 15 pages

Paul Denny, James Prather, Brett A. Becker, Catherine Mooney, John Homer, et al · 2021

Cited alongside, same era.

Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm. In Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems (CHI EA ’21) . Association for Computing Machinery, New York, NY, USA, Article 314, 7 pages

Laria Reynolds and Kyle McDonell. 2021 · 2021

Cited alongside, same era.

Grounded Copilot: How Programmers Interact with Code-Generating Models

Shraddha Barke, Michael B. James, and Nadia Polikarpova. 2022 · 2022

Cited alongside, same era.

Fooling MOSS Detection with Pretrained Language Models. In Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM ’22) . Association for Computing Machinery, New York, NY, USA, 2933–2943

Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models. In Proceedings of the 2022 ACM Conference on International Computing Education Research - Volume 1 (ICER ’22) . Association for Computing Machinery, NY NY, USA, 27–43

Sami Sarsa, Paul Denny, Arto Hellas, and Juho Leinonen. 2022 · 2022

Later among the works it cites.

Solving Probability and Statistics Problems by Probabilistic Program Synthesis at Human Level and Predicting Solvability. In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium , Maria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, and Vania Dimitrova (Eds.). Springer International Publishing, 612–615

Leonard Tang, Elizabeth Ke, Nikhil Singh, Bo Feng, Derek Austin, et al · 2022

Later among the works it cites.

Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models. In CHI Conference on Human Factors in Computing Systems Extended Abstracts . Association for Computing Machinery, NY NY, USA, 1–7

Priyan Vaithilingam, Tianyi Zhang, and Elena L. Glassman. 2022 · 2022

Later among the works it cites.